Data-driven estimation of the sensitivity of target-oriented time-lapse seismic imaging to source geometry

Abstract

The goal of time-lapse imaging is to identify and characterize regions in which the earth’s material properties have changed between surveys. This requires an effective deployment of sources and receivers to monitor the region where changes are anticipated. Because each source adds to the acquisition cost, we should ensure that only those sources that best image the target are collected and used to form an image of the target region. This study presents a data-driven approach that estimates the sensitivity of target-oriented imaging to source geometry. The approach is based on the propagation of the recorded baseline seismic data backward in time through the entire medium and coupling it with the estimated perturbation in the subsurface. We test this approach using synthetic surface seismic and time-lapse VSP field-data from the SACROC field. These tests show that the use of the baseline seismic data enhances the robustness of the sensitivity estimate to errors, and can be used to select data that best image a target zone, thus increasing the signal-to-noise ratio of the image of the target region and reducing the cost of time-lapse acquisition, processing, and imaging.